Image quality assessment through brain signal analysis

Hubert Cecotti; Bryan Gardiner

Image quality assessment through brain signal analysis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Abstract

The presence of noise in images has a key impact on the difficulty of visual target detection tasks. In this study, we propose to explore the potential of brain signal analysis for discriminating the level of noise in a sequence of images. The data were recorded using a magnetoencephalography from four healthy individuals during a rapid serial visual presentation task in four conditions corresponding to four different levels of noise in the images. The results indicate a clear link between behavioural performance, single-trial detection, and noise level.

Original language	English
Title of host publication	Unknown Host Publication
Publisher	Irish Pattern Recognition and Classification Society
Pages	69-70
Number of pages	2
ISBN (Print)	978-0-9934207-1-9
Publication status	Published (in print/issue) - 26 Aug 2016
Event	Irish Machine Vision and Image Processing conference - NUI Galway, Ireland Duration: 26 Aug 2016 → …

Conference

Conference	Irish Machine Vision and Image Processing conference
Period	26/08/16 → …

Keywords

Noise estimation
Brain-Machine Interface
Magnetoencephalography.

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IMVIP2016Book 3Final published version, 713 KB

http://uir.ulster.ac.uk/35735/2/IMVIP%202016%20Acceptance%20-%20Image%20quality%20assessment%20through%20brain%20signal%20analysis.pdf

Cite this

@inproceedings{0993fa7f680e444b9a6af6406469a593,

title = "Image quality assessment through brain signal analysis",

abstract = "The presence of noise in images has a key impact on the difficulty of visual target detection tasks. In this study, we propose to explore the potential of brain signal analysis for discriminating the level of noise in a sequence of images. The data were recorded using a magnetoencephalography from four healthy individuals during a rapid serial visual presentation task in four conditions corresponding to four different levels of noise in the images. The results indicate a clear link between behavioural performance, single-trial detection, and noise level.",

keywords = "Noise estimation, Brain-Machine Interface, Magnetoencephalography.",

author = "Hubert Cecotti and Bryan Gardiner",

year = "2016",

month = aug,

day = "26",

language = "English",

isbn = "978-0-9934207-1-9",

pages = "69--70",

booktitle = "Unknown Host Publication",

publisher = "Irish Pattern Recognition and Classification Society",

address = "Ireland",

note = "Irish Machine Vision and Image Processing conference ; Conference date: 26-08-2016",

}

Cecotti, H & Gardiner, B 2016, Image quality assessment through brain signal analysis. in Unknown Host Publication. Irish Pattern Recognition and Classification Society, pp. 69-70, Irish Machine Vision and Image Processing conference, 26/08/16. <http://uir.ulster.ac.uk/35735/2/IMVIP%202016%20Acceptance%20-%20Image%20quality%20assessment%20through%20brain%20signal%20analysis.pdf>

TY - GEN

T1 - Image quality assessment through brain signal analysis

AU - Cecotti, Hubert

AU - Gardiner, Bryan

PY - 2016/8/26

Y1 - 2016/8/26

N2 - The presence of noise in images has a key impact on the difficulty of visual target detection tasks. In this study, we propose to explore the potential of brain signal analysis for discriminating the level of noise in a sequence of images. The data were recorded using a magnetoencephalography from four healthy individuals during a rapid serial visual presentation task in four conditions corresponding to four different levels of noise in the images. The results indicate a clear link between behavioural performance, single-trial detection, and noise level.

AB - The presence of noise in images has a key impact on the difficulty of visual target detection tasks. In this study, we propose to explore the potential of brain signal analysis for discriminating the level of noise in a sequence of images. The data were recorded using a magnetoencephalography from four healthy individuals during a rapid serial visual presentation task in four conditions corresponding to four different levels of noise in the images. The results indicate a clear link between behavioural performance, single-trial detection, and noise level.

KW - Noise estimation

KW - Brain-Machine Interface

KW - Magnetoencephalography.

M3 - Conference contribution

SN - 978-0-9934207-1-9

SP - 69

EP - 70

BT - Unknown Host Publication

PB - Irish Pattern Recognition and Classification Society

T2 - Irish Machine Vision and Image Processing conference

Y2 - 26 August 2016

ER -

Image quality assessment through brain signal analysis

Abstract

Conference

Keywords

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